How Physics Professors Use and Frame Generative AI Tools

TL;DR

This study explores how physics professors perceive and utilize Generative AI in teaching and research, revealing diverse practices and framing it as both a tool and a threat to academic integrity.

Contribution

It provides qualitative insights into physicists' epistemic framing of GenAI, identifying six distinct perspectives and their implications for physics education and research.

Findings

Professors see GenAI as a coding and text-processing tool.

GenAI is viewed as a knowledge source and discussion partner.

A dominant threat frame influences perceptions of GenAI's role.

Abstract

Generative AI is rapidly reshaping how physicists teach, learn, and conduct research, yet little is known about how physics faculty are responding to these changes. We interviewed 12 physics professors at a major Scandinavian research university to explore their uses and perceptions of Generative AI (GenAI) in both teaching and research. Using the theoretical framework of epistemic framing, we conducted a thematic analysis that identified 19 overlapping practices, ranging from coding and literature review to assessment and feedback. From these practices, we derived six overlapping epistemic frames through which professors make sense of GenAI: as a threat to genuine learning and assessment, a source of knowledge, a discussion partner, a text-processing tool, a coding tool, and a labor-saving device. While the latter five position GenAI as a useful tool in the physicists' toolbox, the threat frame represented an overarching concern that colored all other frames. These findings reveal how GenAI is beginning to transform what it means to be a physicist, highlighting both opportunities for innovation and challenges for academic integrity and learning.